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Compare modelos biológicos, motores de docking y flujos computacionales lado a lado. Filtre por modelo de acceso, huella de cómputo y categoría para obtener una tabla de decisiones útil en menos de un minuto.
| Atributo | ＋ Añadir herramienta | |
|---|---|---|
| Category | Biological AI Models | — |
| Subcategory | Protein Structure | — |
| Company | Google DeepMind | — |
| Access mode | Provider-specific terms | — |
| Licence conditions | Code and model parameters have separate terms. Parameter access must be obtained from the provider; commercial eligibility is not established here. | — |
| Compute requirements | H100 80 GB; CPU/RAM and sequence databases are also required. Larger inputs can require configuration changes. | — |
| Biological application | No registrado | — |
| Research workflow | Predict biomolecular structures | — |
| Evidence level | Provider-tested configuration | — |
| Commercial eligibility | Not independently confirmed | — |
| Price | See provider terms | — |
| Availability ⓘ | Check provider access requirements | — |
| Features | Biomolecular structure prediction, Local inference pipeline | — |
| Entry type | Software / platform | — |
| AI role | AI / computational workflow | — |
| Input data | No registrado | — |
| Output data | No registrado | — |
| Validation | No registrado | — |
| Type | Structure prediction model | — |
| Intended use | No registrado | — |
| Compatibility | No registrado | — |
| Access ⓘ | See code licence and model parameter terms | — |
| Integration evidence | https://github.com/google-deepmind/alphafold3/blob/main/docs/performance.md | — |
| Laboratory handoff | Editorial next step: select an appropriate structural or functional validation assay with the research team. No direct instrument integration has been verified. | — |